This article set out to stress how the national-level time series data was a crude tool for answering criminological questions. It was seen that inferences drawn from aggregate time series estimates have the potential to be misleading. By utilizing one particular methodological approach, statistical methods were made the focus of the research instead of understanding the crime. The aggregate data does not allow for a wide range of covariates, yielding coefficients that do not have a causal interpretation. The article continued by considering the factors that influence the usefulness of aggregate time-series data for understanding a problem and outlined a range of other methodological approaches in analyzing the link between unemployment and crime, such as cross section and panel data analysis of less geographically aggregated areas, natural experiments, international data, individual-level data, and ethnography. Other approaches have their own weaknesses, but collectively they were likely to shed more light on the issues being studied. References